babymore87
MyBoerse.bz Pro Member
Generative AI Marketing, Sales, CX & Revenue Growth
Published 9/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 5h 46m | Size: 7.14 GB
Explore ChatGPT content, AI-powered sales, e-commerce personalization, and practical revenue strategy
What you'll learn
Explain core generative AI capabilities and distinguish them from predictive analytics and conversation intelligence.
Use ChatGPT prompts to structure market research, competitor analysis, and content planning.
Plan and refine advertising campaigns using audience insights, channel choices, testing, and performance metrics.
Draft and repurpose content across platforms while checking facts, brand voice, privacy, and copyright risks.
Map digital customer journeys and identify ways to improve omnichannel engagement, loyalty, and e-commerce conversion.
Evaluate AI-powered personalization, recommendations, product copy, visual assets, and shopping assistants.
Apply AI-assisted prospect research, call insights, sales content, and coaching to improve sales workflows.
Assess use cases for pricing, forecasting, revenue operations, and support with appropriate human oversight.
Outline a staged AI implementation plan using data readiness, prompts or RAG, success metrics, and governance.
Requirements
There are no prerequisites for this course
Description
What if you could use generative AI to uncover amarket opportunity, improve anadvertising campaign, prepare for asales conversation, and makecustomer support more responsive? Those possibilities are exciting-but producing AI output quickly is not the same as making a sound business decision.
Marketing teams still need tounderstand their audiences. Sales teams needaccurate prospect and product information. Retailers needexperiences that work across channels. And every organization needs to know when an AI-generated answer requires a human check. This course brings those challenges together so you can see where generative AI adds value across the customer journey-and where judgment, trustworthy data, and oversight remain essential.
You'll exploreAI applications in market research, advertising, content creation, e-commerce, sales, customer service, pricing, forecasting, and revenue operations. The lectures connect business frameworks with practical use cases, including ChatGPT prompting, campaign testing, conversation intelligence, and AI-supported customer experiences. Case studies such as OkCupid, Diligent Corporation, and Wendy's show how organizations have approached AI adoption in different settings.
In this course, you'll learn how to
- Use AI to support market research, competitor analysis, and strategic planning.
- Plan advertising campaigns and improve them through testing, measurement, and iteration.
- Prompt ChatGPT to develop, edit, and repurpose marketing content across platforms.
- Improve digital customer journeys through omnichannel thinking, personalization, analytics, and conversion optimization.
- Explore AI-powered product recommendations, visual content, and shopping assistants.
- Support prospect research, sales conversations, follow-ups, training, and coaching with AI.
- Evaluate opportunities in pricing, forecasting, RevOps, and customer support.
- Plan AI pilots with clear goals, appropriate data and tools, performance measures, and responsible governance.
This is abusiness-focused course for people who want to make better-informed use of generative AI, not simply generate more output. Whether you work in marketing, sales, digital retail, customer experience, or revenue strategy, you'll leave with a broader view of theopportunities, limitations,anddecisions involved in putting AI to work.
Who this course is for
Marketing, advertising, and content professionals
Sales representatives, managers, and enablement teams
E-commerce and digital retail professionals
Customer experience and customer support leaders
Revenue operations, pricing, and business strategy professionals
Founders and business leaders evaluating AI opportunities
Product and operations managers involved in AI adoption
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